In manufacturing, the supply chain manager is responsible for the flow of goods and services, including all processes that transform raw materials into final products. One critical aspect of this is inventory management. In the most rudimentary (but surprisingly still common) scenario, inventory managers are tasked with counting and logging each piece of inventory, comparing these with the amounts needed, and determining what items need to be replenished, and when. Although on the surface, this appears to be a relatively straightforward task, a deeper examination suggests that inventory management places a heavy load on the cognitive system in the brain, and thus is prone to error.

Consider the inventory manager standing in front of the first collection of items. From a cognitive neuroscience perspective, one first has to count each item. This involves fixating on the first item and incrementing a counter in working memory from 0 to 1. Then an eye movement and attention switch must be initiated from the first item to the second item and the counter must be incremented to 2. Another eye movement and attention switch to the third item ensues, and the process is repeated.

Any time working memory load and executive attentional demands are taxed, one is more likely to make an error
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Critically, the inventory manager must follow some systematic approach to the eye movements and counting process to ensure that they do not miss any items or count items twice. The process of counting and systematic shifts of eye fixation places a heavy burden on working memory and attentional processes. Next, the inventory manager must rehearse the final count in working memory while shifting attention from the actual inventory to the inventory log. On the log, they must find the appropriate location, then write the number down that they have been mentally repeating. This number must then be compared with some threshold number and a decision must be made whether to order more of that inventory item or not, and that decision must, in turn, be logged. The inventory manager moves on to the next inventory item, again in some systematic fashion to ensure counting all of the inventory, and repeats the process all over again.

The cognitive neuroscience research is clear that each of these repetitive steps requires an enormous amount of cognitive capacity (in the form of working memory) as well as cognitive energy (in the form of executive attention). Any time working memory load and executive attentional demands are taxed, one is more likely to make an error and miscount, double count, or forget the count completely and have to start over. Because this process is error-prone, it is impossible to know if the inventory counts are correct and where errors might be.

When it comes to inventory management, the advantages of a hands-free, wearable device should not be underestimated
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To optimize and increase the efficiency of inventory management, the cognitive load on working memory and attention must be reduced. Augmented reality (AR) tools offer significant promise for efficient inventory management because they reduce the cognitive load, and utilize the manager’s visual field and visualization processes in the brain.

Consider the same task, but where the inventory manager is wearing AR glasses. They enter the inventory room and visually scan it. Using visual assets such as text or colored arrows, the AR display directs them to the first set of items. They fixate each item and either manually count the items, or the AR system automatically counts the items. This value is then input into an electronic system either through eye fixations to locations on the AR glasses or through verbal commands.

Budgetary constraints can determine the sophistication of the AR algorithms to be used
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When the inventory is low, a warning is presented and the individual tags that inventory for immediate replenishment, again through eye fixations or verbal commands. Throughout this whole process, the manager is looking toward the inventory with minimal load on working memory and few attention switches. The glasses then direct the individual to the next item and the process is repeated. The path taken through the inventory is optimized to require the minimum number of steps to complete. Attention switching is almost nonexistent because the counting and tabulating tool are always on the AR screen. The cognitive load is minimized because the system is doing most of the calculating and tabulating. The number of physical steps taken by the employee is minimized and optimized by the system. In a nutshell, it works the way our brains work, creating an optimal environment for inventory management with a reduced likelihood of error.

If your organization is considering an AR inventory tool, they come in many forms and budget ranges. Although hand-held AR devices are more budget-friendly than hands-free devices, when it comes to inventory management, the advantages of a hands-free, wearable device should not be underestimated, as the ability to reduce eye movements and attention switches is far superior with a wearable device.

If you are considering do-it-yourself AR authoring tools, be mindful of the risk of cognitive overload
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Beyond that, budgetary constraints can determine the sophistication of the AR algorithms to be used. For example, whether counts are manual or automated, and whether the path through the inventory space is determined by the inventory manager or is optimized by the AR system. Consideration must also be taken to the human factors of the system. Augmented information can reduce the cognitive load, but can also overload the user with unnecessary information.

Look for vendors who address these issues specifically and can present data to support the effectiveness of their offering. If you are considering do-it-yourself AR authoring tools, be mindful of the risk of cognitive overload. Good experimental testing and modification to optimize your tool are in order. Your goal is to provide users with “what” they want, “where” they need it, and “when” they need it.

Tech Trends offers a broad range of Digital Consultancy services to guide companies, individuals, and brands in effectively leveraging existing and emerging technologies in their business strategy.

Todd Maddox is Science, Sports and Training Correspondent at Tech Trends, and the CEO of Cognitive Design and Statistical Consulting. Follow him on Twitter @wtoddmaddox

The post Report: Managing the Supply Chain With AR appeared first on Tech Trends.

Medical devices are essential for safe and effective prevention, diagnosis, treatment and rehabilitation of illness and disease. Many are used in the patient’s home allowing patients to lead normal lives, and to address their health needs on their own or with loved ones. Critically, high-quality education and training on these devices is required to avoid complications resulting from incorrect care and maintenance. For example, the Continuous Positive Airway Pressure (CPAP) system commonly used to treat obstructive sleep apnea, is a complex system that requires sterilization on a daily basis to avoid infection. In addition, poor cleaning and maintenance of a colostomy bag can be life-threatening. Finally, medical devices such as in-home peritoneal dialysis machines to address kidney disease, and insulin infusion pumps to treat diabetes are central to patient care, but these systems must be maintained to avoid complications. Although the existence of these medical devices increases the patient’s freedom and quality of life by allowing them to be treated at home, medical personnel are not readily available should something go wrong. This makes quality education and training critical to success.

High-quality education and training on medical devices is required to avoid complications resulting from incorrect care and maintenance
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By far the most common approach to medical device education is to have patients read documents describing the device and outlining the steps needed to care and maintain the device. Patients are expected to study and memorize the steps so that they can effectively care and maintain the device and avoid complications. This approach leaves it to the patient to determine proficiency and leaves the patient at risk when proficiency has not been achieved. With more complex systems, such as a peritoneal dialysis machine, document training will be supplemented with classroom and hands-on training with an expert. Although clearly superior to document training alone, this is time-consuming, costly, and is difficult to scale.

Patients are expected to study and memorize the steps so that they can effectively care and maintain the device and avoid complications
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The neuroscience of learning and performance suggests that this traditional approach to medical device training is sub-optimal for at least two reasons. First, document training focuses almost exclusively on cognitive learning, when what is needed is broad-based experiential and behavioral learning. Second, hands-on training with an expert, although effective, is rarely extensive enough to ensure broad-based proficiency.

In this report, we discuss the neuroscience of learning and performance. We show why traditional approaches to medical device training are sub-optimal and can leave patients vulnerable to complication. We also show how immersive technologies like virtual reality (VR) and augmented reality (AR) hold great promise for optimizing medical device training.

The neuroscience of learning and performance suggests that this traditional approach to medical device training is sub-optimal
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As outlined in the figure below, the human brain is comprised of at least four distinct learning systems: experiential, cognitive, behavioral and emotional. As alluded to by Einstein, experience is at the heart of learning, and forms the foundation of VR and AR. The experiential system represents the sensory and perceptual aspects of an experience, whether visual, auditory, tactile or olfactory. Because every experience is unique and is immersive, this adds rich context and nuance to the learning. These enhance generalization and transfer of learning. The critical brain regions associated with experiential learning are the occipital lobes (sight), temporal lobes (sound), and parietal lobes (touch).

Hands-on training with an expert, although effective, is rarely extensive enough to ensure broad-based proficiency
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In this report, we discuss the neuroscience of learning and performance
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The cognitive system is the information system. This is the “everything else” that Einstein noted. The cognitive system processes and stores knowledge and facts that usually come in the form of text, graphics, or video. The cognitive system is truly amazing and is more developed in humans than in any other organism, but it relies on working memory and attention that are limited resources and form a bottleneck that slows learning. More information comes into the system and is available to the learner (the green arrows) than can be processed (the red arrow). This system encompasses the prefrontal cortex and hippocampus. Importantly, this system is slow to develop and starts to decline in middle age when health issues begin to arise.

The behavioral system in the brain has evolved to learn motor skills. It is one thing to memorize the steps needed to care and maintain a medical device, but it is completely different (and mediated by different systems in the brain) to know how to perform those steps. The behavioral learning system is fascinating, but its detailed processing characteristics are beyond the scope of this report. Suffice it to say that processing in this system is optimized when behavior is interactive and is followed in real-time (literally within milliseconds) by corrective feedback. Behaviors that are rewarded lead to dopamine release into the striatum that incrementally increases the likelihood of eliciting that behavior again in the same context. Behaviors that are punished do not lead to dopamine release into the striatum thus incrementally decreasing the likelihood of eliciting that behavior again in the same context.

This broad-based neural activation leads to a highly interconnected, context-rich set of learning and memory traces
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The emotional learning system in the brain has evolved to facilitate the development of situational awareness — the ability to read nuance in a situation, to know what comes next, and to deal effectively with stress, pressure, and anxiety. This system affects processing in the cognitive and behavioral systems and helps patients learn to care and maintain medical devices under stress or pressure, or when “things just aren’t going right”. The critical brain regions are the amygdala and other limbic structures. Emotional learning is at the heart of situational awareness.

Using an insulin infusion pump as an example, let’s explore the traditional approach to training. The patient starts by reading documents that outline step-by-step how to care, maintain, and use the insulin pump. Then the patient may receive some hands-on training where they observe as an expert cleans and sets the pump up for usage. The patient may be given the opportunity to demonstrate the steps to the expert while receiving feedback. Because hands-on training is so time-intensive and costly, document and do-it-yourself training is usually emphasized.

These highly interconnected memory traces will be slower to decay over time leading to better long-term retention
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From a neuroscience perspective, this approach starts by engaging the cognitive system as the patient reads documents and attempts to memorize the steps. Because the infusion pump is a 3-dimensional object and the system is dynamic (pushing insulin into the body), it is challenging to fully understand how the system works when the information being processed by the patient is 2-dimensional, static, and usually text-based. The patient must convert 2-dimensional static information into a 3-dimensional dynamic mental representation in the brain that accurately reflects the operation of the infusion pump. The cognitive effort needed to do this is enormous. Given the fact that working memory and attention are limited capacity resources, this process with be slow, challenging, and error-prone.

During the hands-on training, the patient can “experience” the system in action while watching an expert. This combines experiential learning with cognitive learning. When the patient is given a chance to care and maintain the device while receiving corrective feedback from the expert, behavioral learning is added to the mix. Although effective, behavioral learning is gradual and incremental and proficiency takes extensive practice, usually more than is provided in traditional training settings. In addition, it is rare that uncommon situations are trained.

Because XR training tools are available 24/7 the patient can have unlimited practice, and can train and test themselves under a broad range of environmental conditions
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At some point, the patient is deemed “ready” and they are allowed to take the infusion pump home. It is at this stage when the patient is at the greatest risk. They have a basic understanding of the care and maintenance of the infusion pump, but do not have extensive experience, and lack confidence. The brain tells us why. All of the training has been sequential and disjointed. Training starts with documents that train the cognitive system. Experience is then added to the mix, with behavioral training occurring last. What the patient really needs is for cognitive, experiential and behavioral learning to occur simultaneously, and in the environment where the infusion pump will be used (i.e., in the home). In addition, they need situational awareness training to deal with cases in which they are under stress or pressure, or when things are not going according to plan.

Now consider an immersive approach to infusion pump training. Suppose the patient dons a VR headset and is immersed in a 360 experience with an expert who has used an infusion pump for years. The patient can watch as the expert demonstrates and verbally describes the step-by-step procedures needed to care and maintain the infusion pump. The patient can view this from a third-person perspective, but also from the first-person perspective. The expert can demonstrate common pitfalls and how to address them, while describing them verbally. The expert can do all of this while demonstrating a calm demeanor. The patient can view the VR experience and can complete knowledge checks at the end to ensure that they have the requisite knowledge. They can view the experience as many times as they like until they are confident in their own skills.

With XR training, the patient can view the experience as many times as they like until they are confident in their own skills
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To train the behavioral aspects of infusion pump care and maintenance, one could utilize an interactive VR setup, or an AR solution. Imagine using your tablet or a hands-free AR device that uses computer vision to identify the make and model of your infusion pump. The AR system uses visual assets such as arrows, highlights, text and such to guide you step-by-step through the care and maintenance of the system. As each step is completed, you are rewarded with success and move on to the next step in the process. You can practice the process as many times as you like, and even under time pressure.

From a neuroscience perspective, this immersive VR/AR approach engages all four learning systems in synchrony. In AR, assets are providing the necessary cognitive information. The learning is happening in real-time and through experience, with the patient generating the relevant behaviors and being rewarded or punished. This broad-based neural activation leads to a highly interconnected, context-rich set of learning and memory traces. These highly interconnected memory traces will be slower to decay over time leading to better long-term retention. Because these VR and AR training tools are available 24/7 the patient can have unlimited practice, and can train and test themselves under a broad range of environmental conditions. If they are unsure of a step, they simply pull out their VR headset or tablet, start the VR or AR software and are guided through the relevant steps.

From a neuroscience perspective, this immersive XR approach engages all four learning systems in synchrony
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Gone will be the days where medical device training for patients is inadequate, and patients are at risk of complication. With immersive technologies, patients can be given standardized and highly effective training from day 1. They can obtain experiential familiarization and practice as many times as they like. They can receive training on rare, but life-threatening situations so that they are prepared for anything. Because these immersive technologies broadly engage multiple learning systems in the brain in synchrony, the patient will obtain a strong knowledge base and behavioral repertoire that have been honed and testing. Patients will be more satisfied and confident, and fewer complications will arise.

With immersive technologies, patients can be given standardized and highly effective training from day 1
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For companies looking to get into Immersive technologies such as VR/AR/MR/XR our Virtual Reality Consultancy services offer guidance and support on how best to incorporate these into your brand strategy.

Todd Maddox is Science, Sports and Training Correspondent at Tech Trends, and the CEO of Cognitive Design and Statistical Consulting. Follow him on Twitter @wtoddmaddox

The post Report: XR Medical Device Training appeared first on Tech Trends.

Todd Maddox reports on why A/B tests are sub-optimal in building and optimizing immersive training and performance tools.

As with any young science or technology, the early wins are often large, but more wins are to follow if solid research and development is conducted that leverages what we know about the brain
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I have written extensively on the potential of virtual reality (VR) and augmented reality (AR) to revolutionize training and performance in healthcare, manufacturing, and corporate learning, to name a few. Learning is about the experience, and VR and AR are grounded in experiential learning. VR offers a virtual experience and AR overlays computer-generated assets onto the real world to drive learning and performance.

Learning is about the experience, and VR and AR are grounded in experiential learning
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Unfortunately, too often the primary focus is on the technology, with much less focus on optimizing the interface and the experience for the user (the UI/UX). Although computing power, specialized graphics, controllers, and the like are important, their value is diminished if they don’t engage the user’s brain in a way that is effective at achieving the desired training and performance goal. Too often the technological “wow” factor dominates when what is more important is how the user’s brain is engaged to achieve a set goal.

VR offers a virtual experience and AR overlays computer-generated assets onto the real world to drive learning and performance
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To optimize the UI/UX we must incorporate what is known about the brain and how it processes information, then apply the scientific method to test hypotheses and to identify the optimal solution. For example, one might test the hypothesis that a hands-free AR training solution leads to faster task completion than a hand-held AR training solution. To test this hypothesis, suppose that 10 workers completed the task with the hands-free AR solution, and 10 other workers completed the task with the hand-held AR training solution.

Unfortunately, too often the primary focus is on the technology, with much less focus on optimizing the interface and the experience for the user
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Under the assumption that the only difference between the two groups of workers is the type of training device, the time to completion would be noted for each of the 20 workers and a simple statistical test (called a Student’s t-test) would be conducted to compare the time to completion between the two groups. Although a detailed description of probability theory that underlies statistical reasoning is beyond the scope of this report, suffice it to say that the outcome of this statistical test allows one to claim (or not claim) beyond a “statistical reasonable doubt” that the hands-free AR solution leads to faster time to completion than the hand-held AR solution.

Too often the technological “wow” factor dominates when what is more important is how the user’s brain is engaged
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The experiment described above is referred to as an A/B test in the corporate sector. It is the simplest type of experiment that can be conducted, but it is extremely powerful and is used extensively. If you want to determine whether a new drug has the desired effect, you might conduct an A/B tests of the drug against a placebo. If you want to determine if your new technology or product is superior to the existing gold standard, you might conduct an A/B test. An A/B test allows you to test the hypothesis that one group is different from another on some outcome measure, such as time to completion.

To optimize the UI/UX we must incorporate what is known about the brain and how it processes information
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I spent 25 years teaching statistics and experimental design to University students, and during that time, I conducted 100s of experiments in my laboratory. I can count on one hand the number of A/B tests that I conducted.

An A/B test allows you to test the hypothesis that one group is different from another on some outcome measure, such as time to completion
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Why so few?

Although there is nothing wrong with an A/B test, factorial designs provide more value at no additional cost. In an A/B test there is one factor. In the example above, the factor would be the type of AR training device (hands-free vs. hand-held). Suppose a second factor was included that represented time pressure. Specifically, suppose that 5 of the workers using the hands-free device and 5 of the workers using the hand-held device were simply told to complete the task, whereas the other 5 from each group were told that they must complete the task within 15 minutes when it normally takes about 25 minutes. This factorial design has four groups of workers: hands-free/no time pressure, hands-free/time pressure, hand-held/no time pressure, and hand-held/time pressure. More importantly, it allows one to test three hypotheses.

• Hypothesis 1: Does a hands-free device speed time to completion?
• Hypothesis 2: Does time pressure speed or slow time to completion?
• Hypothesis 3: Does the presence or absence of time pressure affect time to completion differently for hands-free vs. hand-held AR training tool?

Although there is nothing wrong with an A/B test, factorial designs provide more value at no additional cost
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In the simple A/B test example, 20 workers completed the task, and Hypothesis 1 was tested. In the factorial design example, 20 workers completed the task and all three hypotheses could be tested. This is the power of a factorial design over an A/B test, and this is one reason why the overwhelming majority of experimental science, especially behavioral science, relies exclusively on factorial designs. A second reason follows from Hypothesis 3.

Hypothesis 3 is especially interesting and addresses the possibility that there is an “interaction” between time pressure and the nature of the device on time to completion. I would predict that a hands-free device is much less susceptible to the deleterious effects of time pressure than a hand-held device. Of course, this is an empirical question.

Interactions abound in the real world, especially the world of behavioral science. We have all heard of drug interactions. For example, some research suggests that a glass or two of wine can reduce stress, and a small dose of Xanax can reduce anxiety, but combining alcohol and Xanax can be fatal. That is a drug interaction. The combined effect of alcohol and Xanax is not simply the sum of the independent effects. Rather the effect is interactive, large, and potentially fatal.

Interactions abound in the real world, especially in behavioral science
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Anytime a human is involved and is physically processing something like a drug, or is mentally processing and engaging with technology, interactions are likely. This is the second reason why factorial designs are so popular. You will miss important findings if you focus exclusively on A/B tests.

The behavioral skills learning and performance system in the brain relies on the striatum and learns stimulus-response associations via incremental, dopamine-mediated reward and punishment learning
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The human brain is composed of multiple learning and performance systems. These include the cognitive learning and performance system in the brain that relies on the prefrontal cortex and is constrained by working memory and attentional limitation. The behavioral skills learning and performance system in the brain relies on the striatum and learns stimulus-response associations via incremental, dopamine-mediated reward and punishment learning. Interestingly, this system is not constrained by working memory and attention. In fact, “overthinking” hurts behavioral learning.

he emotional learning and performance system in the brain relies on the amygdala and other limbic structures
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The emotional learning and performance system in the brain relies on the amygdala and other limbic structures. This addresses issues of stress, pressure, and situational awareness broadly speaking. Finally, the experiential learning and performance system in the brain represents the sensory and perceptual aspects of the environment and relies on the occipital, temporal, and parietal lobes.

Anytime a human is mentally processing and engaging with technology, interactions are likely
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Each system has its own unique processing characteristics, and thus each system is optimized with different technologies and processes. For example, the critical bottleneck within the cognitive system is cognitive load. One almost always wants to reduce cognitive load. This means that the what, where, and when of VR or AR assets must be examined to determine the optimal combination to achieve a given goal. The best way to do this is with a factorial design.

VR and AR training and performance tools have already provided significant ROI relative to traditional training approaches
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The what, where, and when are each a separate factor that must be combined and studied factorially to optimize performance. The nature and timing of corrective feedback in the behavioral system must be examined with a factorial design, and of course the emotional and motivational aspects (stress, pressure, engagement) as well as the detailed sensory and perceptual processes must be examined.

You will miss important findings if you focus exclusively on A/B tests
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The basic science literature is full of fascinating results in each of these domains that can guide VR and AR product optimization, but in the end, one has to rely on science and factorial designs to “get it right”. The plethora of data that can be extracted from VR and AR solutions and the ease of manipulating relevant factors (what, where and when of assets or the nature of timing of the feedback) makes factorial designs straightforward to conduct.

The plethora of data that can be extracted from VR and AR solutions and the ease of manipulating relevant factors makes factorial designs straightforward to conduct
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VR and AR training and performance tools have already provided significant ROI relative to traditional training approaches. If you have a basic understanding of the breadth of neural engagement with these technologies, then you are not surprised by this ROI. Even so, these initial ROI benchmarks are a starting point. Much more ROI is awaiting those organizations who are ready to conduct the factorial design experiments necessary to find the “sweet spots” in the UI/UX, and there are many, that will show the true value of these technologies.

The nature and timing of corrective feedback in the behavioral system must be examined with a factorial design
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These immersive training and performance technologies are still in the early stage. They are reaping benefits for their users because of the way that they engage the brain relative to traditional approaches. As with any young science or technology, the early wins are often large, but more wins are to follow if solid research and development is conducted that leverages what we know about the brain, applies the scientific method, and uses factorial designs as a window onto the interactions that optimize UI/UX.

The basic science literature is full of fascinating results in each of these domains that can guide VR and AR product optimization
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For companies looking to get into Immersive technologies such as VR/AR/MR/XR our Virtual Reality Consultancy services offer guidance and support on how best to incorporate these into your brand strategy.

Todd Maddox is Science, Sports and Training Correspondent at Tech Trends, and the CEO of Cognitive Design and Statistical Consulting. Follow him on Twitter @wtoddmaddox

The post Building Better XR Training appeared first on Tech Trends.

Todd Maddox delves into the Neuroscience behind immersive technologies’ unique ability to make us experience things from another person’s perspective.

Merriam-Webster defines empathy as “the action of understanding, being aware of, being sensitive to, and vicariously experiencing the feelings, thoughts, and experience of another…without having these fully communicated in an objectively explicit manner.”

Any profession that requires interpersonal interaction, such as education, retail, food service, and call centers, is better served with strong empathy
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That is a lot to unpack, but it is clear that empathy is about much more than an explicit cognitive understanding of someone’s situation. It is more about an emotional, experiential and visceral understanding as if you have “walked a mile in someone else’s shoes” and have shared their experiences. Empathy also shows in one’s behavior. An empathetic individual uses open body language and a verbal tone that shows genuine behavioral intent. Empathy is something that you can see in another’s action.

An empathetic individual uses open body language and a verbal tone that shows genuine behavioral intent
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In this report, I review the psychology and neuroscience of learning and show that virtual reality (VR) has the potential to build empathy in individuals. As outlined above, this requires training at an emotional, experiential and behavioral level, not just at a cognitive level. Empathy building is facilitated by immersive experiences that are rich in context and emotion and allow one to “walk a mile in someone else’s shoes”. As I show below, VR meets these challenges.

Empathy is something that you can see in another’s action
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Empathy is important in life and in many professions, and it is especially important in professions that help people in need or people under duress. For example, empathy is critical in healthcare, social work, senior care, and law enforcement, to name a few. In fact, any profession that requires interpersonal interaction, such as education, retail, food service, and call centers, is better served with individuals having strong empathy. Anytime someone could “use a friend”, “someone to listen”, or “someone to care and connect with”, empathy is a must.

Although there is likely some genetic component to empathy, as there is with so many things, many believe that it can be trained
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Some people seem to naturally have empathy, and others seem not to. Although there is likely some genetic component to empathy, as there is with so many things, many believe that empathy can be trained. Empathy training is clearly challenging though because this is not a skill that requires a simple cognitive understanding. Rather, empathy is an emotional skill that requires shared experience in the sense that one can “walk a mile in someone else’s shoes, and can behave accordingly.

Empathy training is about training a person, and every person’s actions are directed by their brain. Thus, to understand how to effectively train empathy, one must understand the psychology and neuroscience of learning.

“Learning is an experience. Everything else is just information”

Albert Einstein

This is an insightful quote from Albert Einstein that is supported by the neuroscience of learning and is especially relevant to empathy training.

As outlined in the figure below, the human brain is comprised of at least four distinct learning systems. As Einstein so eloquently stated, experience is at the heart of learning. The experiential system has evolved to represent the sensory aspects of an experience, whether visual, auditory, tactile or olfactory. Every experience is unique, adds rich context to the learning and is immersive. The critical brain regions associated with experiential learning are the occipital lobes (sight), temporal lobes (sound), and parietal lobes (touch/smell). Experiential learning is especially important when it comes to empathy. The more one can vicariously experience the feelings, thoughts, and experiences of another, the more empathetic they will become. If one can literally “walk a mile in someone else’s shoes” they get this vicarious experience.

Empathy building is facilitated by immersive experiences rich in context and emotion that allow one to walk a mile in someone else’s shoes
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One can experience a situation from any vantage point; Providing empathy, watching another provide empathy or receiving empathy
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The cognitive system is the information system. It processes and stores knowledge and facts using working memory and attention. Critically, these are limited resources and form a bottleneck that slows learning with more information coming in and available to the learner (the green arrows) than can be processed (the red arrow). This system encompasses the prefrontal cortex and hippocampus. This is the “everything else” aspect of learning that Einstein alluded to. With respect to empathy, this might involve memorizing the Merriam-Webster definition, knowing explicitly that eye contact is important, or that it is important to be understanding.

The behavioral system in the brain has evolved to learn motor skills. This is an amazing system and one that builds the “muscle memory” that drives empathetic behaviors. The detailed processing characteristics of this system are fascinating but are beyond the scope of this report. Suffice it to say that the critical brain structure for behavioral learning is the striatum, and processing in the striatum is optimized when behavior is interactive and is followed in real-time (literally within milliseconds) by corrective feedback. Behaviors that are rewarded lead to dopamine release into the striatum that incrementally increases the likelihood of eliciting that behavior again in the same context.

emotional learning, when combined with context-rich experiences, builds rich repertoires of empathetic understanding and behavior
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Behaviors that are punished do not lead to dopamine release into the striatum thus incrementally decreasing the likelihood of eliciting that behavior again in the same context. This system links rich experiential contexts (represented by the experiential learning system) and emotions with the appropriate behavioral responses. It is one thing to know the definition of empathy, to know that eye contact is important, and to know that you need to show understanding, but it is completely different (and mediated by different systems in the brain) to know how to show empathy with eye contact and behaviors that demonstrate true understanding.

The more one can vicariously experience the feelings, thoughts, and experiences of another, the more empathetic they will become
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More than anything, it is the emotional learning system in the brain that builds the interpersonal understanding, awareness, and sensitivity that are at the heart of empathy and an understanding of our and others’ behaviors. The critical brain regions are the amygdala and other limbic structures. The detailed processing characteristics of this system are less well understood than the cognitive and behavioral skills learning systems, but emotional learning, when combined with context-rich experiences, builds rich repertoires of empathetic understanding and behavior.

The emotional learning system in the brain builds the interpersonal understanding, awareness, and sensitivity that are at the heart of empathy and an understanding of our and others’ behaviors
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It should be clear from this brief review of the psychology and neuroscience of learning, that training empathy is a challenge. Memorizing definitions, and an explicit cognitive understanding of empathy is not sufficient. Watching video of examples of empathetic and non-empathetic behavior is better, but even these do not represent immersive, context-rich experiences that elicit strong emotions. Empathy simulation and role-play training offer a step in the right direction because they are interactive, involve emotion-laden situations and behavior, but even here it is often difficult to suspend the reality of who you are and who your role-playing partner might be. In addition, people differ in their willingness and ability to role play. Finally, simulation and role play are time-consuming, costly, and not scalable.

This is where VR comes in. VR is time- and cost-effective, and is scalable. One can experience numerous VR scenarios and can repeat them as many times as one likes. VR has the potential to build the empathy that is so desperately needed.

VR is time- and cost-effective, and is scalable
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One can experience numerous VR scenarios and can repeat them as many times as one likes
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Consider a healthcare setting and a nurse-in-training. As any seasoned nurse will tell you, the classroom does a good job of training the technical aspects of the job, but not the interpersonal. However, suppose this nurse-in-training was given empathy training in VR, along with their traditional classroom training. Using VR, this nurse-in-training might be transported into the middle of a busy emergency room and shadow a seasoned nurse explaining a patient’s condition to their distraught spouse. Using voice-over, the seasoned nurse might explain how they are showing empathy to soothe the concerns of the spouse. The nurse-in-training is in the situation and can feel the emotions. They can combine the information provided by the seasoned nurse with the behaviors they are observing, all within an emotion-laden, realistic experience.

A nurse-in-training might be transported into the body of a patient just coming out of anesthesia following surgery
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This engages multiple learning systems in synchrony and will build empathy quickly and effectively. Analogously, the nurse-in-training might be transported into the body of a patient just coming out of anesthesia following surgery. They might experience one situation in which their nurse shows strong empathy and another situation in which their nurse does not. These behaviors are being directed at the nurse-in-training, while they embody a patient. This “walk a mile in my shoes” experience offers the first-person perspective that one needs to build empathy.

VR has the potential to build the empathy that is so desperately needed
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One can imagine similar VR empathy building scenarios for social workers, senior care professionals, law enforcement, retail, food service, and education to name just a few.

VR is immersive, and with high-quality content, one can experience almost any empathy-building situation. The experiential learning systems will be highly engaged and the learner will have a sense of presence. One can experience a situation from any vantage point, whether the one providing empathy, one watching another provide empathy or the receiver of empathy. Thus, one can obtain an emotional understanding from multiple perspectives. A cognitive understanding can emerge, but it is a byproduct and not the primary avenue of training. Emotion-laden experiential learning builds a deep emotional understanding of empathy, while simultaneously building a strong repertoire of empathy-related behaviors.

VR is immersive, and with high-quality content, one can experience almost any empathy-building situation
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For companies looking to get into Immersive technologies such as VR/AR/MR/XR our Virtual Reality Consultancy services offer guidance and support on how best to incorporate these into your brand strategy.

Todd Maddox is Science, Sports and Training Correspondent at Tech Trends, and the CEO of Cognitive Design and Statistical Consulting. Follow him on Twitter @wtoddmaddox

The post Report: VR as an Empathy Builder appeared first on Tech Trends.

A critical function in nearly all industrial and manufacturing settings is to provide high-quality and effective training in environmental health and safety (EHS). Although one might argue that EHS is not the most exciting or engaging topic, a strong understanding of EHS guidelines and most importantly an ability to ACT quickly and effectively under ANY CONDITIONS, including high stress and pressure, can be the difference between a smooth-running operation with only minor safety issues, and an environmental disaster.

The goal of this system is to train direct neural connections between sensory regions and motor regions in the brain that drive behavior
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The terms “act” and “any conditions” are emphasized for a reason. It is one thing to know “what” to do, to have the cognitive ability to verbalize the EHS guidelines, and to pass a written compliance test, but it is another thing (and mediated by different learning and performance systems in the brain) to know “how” to do it, and to be able to perform those behaviors under any conditions, including under high stress or pressure (referred to as situational awareness). The ability to verbalize and pass written tests is important for communication and compliance concerns, but the ability to behave appropriately regardless of the level of chaos and stress, is often the difference between life and death.

The key to xR technologies for training is that they are experience-based
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Because the learning systems in the brain that mediate a cognitive understanding of EHS are distinct from those that mediate a behavioral understanding of EHS and situational awareness, there is very little transfer of cognitive knowledge into behavioral understanding or situational awareness. This is a serious problem in EHS because the majority of EHS training targets a cognitive and not a behavioral understanding.

In this brief report I show that extended reality (xR) technologies hold great promise for training behavior and situational awareness in EHS. xR technologies reduce the burden on cognitive systems whose processing is adversely affected by stress and pressure, provide the opportunity for limitless behavioral practice in virtual or real-world settings, and speed learning and retention by broadly engaging multiple learning systems in the brain in synchrony.

Brain Science of Learning in EHS

The key to xR technologies for training is that they are experience-based. As Albert Einstein so eloquently stated

“Learning is an experience. Everything else is just information”

Experiential learning provides the foundation for the effectiveness of augmented reality (AR) and virtual reality (VR) applications in EHS. As elaborated below, experiential learning is effective because it facilitates the engagement of multiple learning systems in the brain in synchrony.

The human brain is comprised of at least three distinct learning systems. A schematic of the learning systems is provided in the figure below. The cognitive skills learning system in the brain has evolved to obtain and process knowledge and facts. Whether studying the EHS rules and regulations, reading text or watching a video showing you how to test and don a respirator, or taking a compliance test, the cognitive skills learning system is being recruited. Cognitive skill learning tends to involve processing text and schematics and is limited by the learner’s working memory and attention span. It requires focus and mental repetition for long-term memory storage. The cognitive skills learning system encompasses the prefrontal cortex, hippocampus and associated medial temporal lobe structures in the brain. The ultimate goal of this system is to transfer knowledge from short term memory in the prefrontal cortex to long term memory in the hippocampus and medial temporal lobes. Processing in this system is adversely affected by stress, pressure, and anxiety. The cognitive skills system is slow to develop, not reaching maturity until individuals are in their 20’s, and begins to decline in middle age.

The human brain is comprised of at least three distinct learning systems
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A critical function in nearly all industrial and manufacturing settings is to provide high-quality and effective training in environmental health and safety
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The behavioral skills learning system in the brain has evolved to learn behaviors. It is one thing to know what to do, but it is completely different to know how to do it. Knowing the safety rules and regulations is completely different from knowing how to initiate those behaviors in an emergency. Memorizing the location of the fire equipment and the steps to take to use it is completely different from being able to take the shortest path to the equipment and quickly and accurately engaging the equipment in fighting a fire. Behavioral skills are learned by doing. Processing in this system is optimized when behavior is interactive and is followed in real-time (literally within milliseconds) by corrective feedback. Behaviors that are rewarded will be more likely to occur in the future, and behaviors that are punished will be less likely to occur in the future. Interestingly, this system does not rely on working memory and attention, and “overthinking it” hinders behavioral skills learning. Behavioral skill learning is mediated by the basal ganglia and gradual, incremental dopamine-mediated changes in behavior. The ultimate goal of this system is to train direct neural connections between sensory regions and motor regions in the brain that drive behavior.

One advantage of VR is that you can be transported into any situation, including chaotic situations in which you will need to make fast and accurate decisions under pressure
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The experiential learning system has evolved to represent the sensory aspects of an experience, whether visual, auditory, tactile or olfactory. Every experience is unique and adds rich context to cognitive and behavioral skills learning. Experiential learning (in combination with emotional learning systems; not displayed in the figure above) is the key to situational awareness. By training individuals under a broad array of setting including those that occur infrequently, those that involve chaotic and high-stress conditions, or those that require quick action, you are training the broad-based situational awareness that is critical in EHS. It is the nuance and unique aspects of an experience that lead to generalized learning and transfer from the specific training scenario to other related situations that develops situational awareness. The critical brain regions associated with experiential learning differ as a function of the sensory input. Visual representations are formed in the occipital lobes and auditory representations are formed in the temporal lobes. Tactile representations are formed in the parietal lobes and olfactory information is represented in the piriform cortex and olfactory bulb.

Some xR Applications in EHS

Suppose you work in a chemical plant with a large number of flammable chemicals. Should a fire break out, there are a number of steps that you must follow to contain the blaze. This includes:

• taking the shortest path from your current location to the fire suppression equipment
• donning some protective gear
• connecting some hoses, flipping some switches
• returning to the blaze via the shortest path, and
• directing the fire extinguisher directly at the fire

To “learn” these steps you could read a manual with text and figures. This places a heavy load on working memory and attention to translate the abstract information into a visual representation of the steps you would need to take during a fire. Alternatively, you could read the manual and also watch a video that demonstrates the steps being taken by an actor or via animation. This is better because the experiential systems in your brain are being engaged to some degree. However, in both cases, you are likely sitting at a desk and are attempting to store this information in memory for use later during a real-world situation in which your and your co-worker’s safety is in jeopardy from a chemical fire.

Alternatively, suppose an AR tool, such as a Hololens, is used during training. You pick a random location on the factory floor, don the Hololens and start the AR fire training protocol. The system knows your location and tracks your movements. Using visual cues like colored arrows, you are directed to the fire suppression equipment via the shortest possible path. You are given step-by-step directions (verbally, visually, or both) on how to don the appropriate safety equipment, prepare the fire suppression equipment, and are then directed to the fire. Once at the fire, visual cues are provided that direct you on how to start the equipment. This whole process is timed, the system notes what steps you performed correctly and incorrectly, and all of this information is made available to you and your supervisor. In this case, you are “learning by doing” with step-by-step guidance and feedback being provided. You are not only gaining a cognitive understanding of the steps to take, but you are being trained simultaneously on the relevant behaviors. You can repeat this process periodically from different locations on the factory floor, and at some point, you can be tested without the AR cues.

An AR tool could also be used to provide general training on all of the safety equipment in the plant. You might don some AR glasses that direct you to predefined locations in the workplace. At each location, your view of the workplace is augmented with static text overlays or dynamic video that provides specific information on the safety guidelines or usage of safety tools. For specific safety equipment, you could receive step-by-step instructions or visual labels describing exactly how the equipment works. You might then be asked to demonstrate your skill with a specific safety tool, with or without text-based prompting and receive real-time feedback.

An AR tool could be used to provide general training on all of the safety equipment in the plant
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VR tools are also effective for EHS training. One advantage of VR is that you can be transported into any situation, including chaotic situations in which you will need to make fast and accurate decisions under pressure. For example, you might don a VR headset and be transported into the middle of a workplace emergency. You might scan your virtual environment watching personnel follow or fail to follow the guidelines within this chaotic situation while receiving auditory feedback on the appropriate actions. VR also allows you to experience rare, but potentially catastrophic situations, such as a chemical explosion or chemical spill.

In these AR and VR examples, there is minimal need to translate abstract text or figures into a visual representation because this information is being supplemented with experiential learning that is proximal and salient. Because multiple brain systems are active, the memory traces in each system are strong and interconnected. Behavioral learning will also occur when you demonstrate your skill with safety tools and receive feedback either with the AR tool, or in VR with haptic feedback incorporated. The applications of xR technology in EHS are many.

For companies looking to get into Immersive technologies our VR Consultancy service offers comprehensive support in strategic deployment of Virtual, Augmented and Mixed Reality

Todd Maddox is Science, Sports and Training Correspondent at Tech Trends, and the CEO of Cognitive Design and Statistical Consulting. Follow him on Twitter @wtoddmaddox

The post Report: XR Health and Safety Training appeared first on Tech Trends.